Papers with Code 아카이브

Fairness

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

1

평가표

9

보존된 평가 기록

10

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/shayanmohajer/ota-ffl

공식 코드

Over-the-Air Fair Federated Learning via Multi-Objective Optimization

https://github.com/shenghaowu/counterfactual-generative-models

공식 코드

Counterfactual Generative Models for Time-Varying Treatments

https://github.com/shivi98g/Fair-k-means-Clustering-via-Algorithmic-Fairness

공식 코드

Efficient Algorithms For Fair Clustering with a New Fairness Notion

https://github.com/shivtavker/constrained-classification

공식 코드

Consistent Multiclass Algorithms for Complex Metrics and Constraints

https://github.com/shizhouxing/local-lipschitz-constants

공식 코드

Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation

https://github.com/shoyua/towards-reward-fairness

공식 코드

Towards Reward Fairness in RLHF: From a Resource Allocation Perspective

https://github.com/shreyasc-13/suno

공식 코드

Distributional Off-Policy Evaluation for Slate Recommendations

https://github.com/siamakghodsi/ifairnmtf

공식 코드

Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering

https://github.com/sibirbil/RuleDiscovery

공식 코드

Rule Generation for Classification: Scalability, Interpretability, and Fairness

https://github.com/sid-devic/multicalibration

공식 코드

When is Multicalibration Post-Processing Necessary?

https://github.com/simon-tan/laplace

공식 코드

LaPLACE: Probabilistic Local Model-Agnostic Causal Explanations

https://github.com/simondevos/umct

공식 코드

Uplift modeling with continuous treatments: A predict-then-optimize approach

https://github.com/siqixu/deepmed

공식 코드

DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning

https://github.com/sisinflab/elliot

공식 코드

Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

https://github.com/sivansabato/unfairness

공식 코드

Fairness and Unfairness in Binary and Multiclass Classification: Quantifying, Calculating, and Bounding

https://github.com/siyi-wind/FairDisCo

공식 코드

FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning

https://github.com/slkdfjslkjfd/fl_fairness_attacks

공식 코드

Attacks on fairness in Federated Learning

https://github.com/smaityumich/individual-fairness-testing

공식 코드

Statistical inference for individual fairness

https://github.com/smallporridge/trustworthyrag

공식 코드

Trustworthiness in Retrieval-Augmented Generation Systems: A Survey

https://github.com/smith-pit/llm-partisan-bias

공식 코드

Whose Side Are You On? Investigating the Political Stance of Large Language Models

https://github.com/so-cool/crossmodelfairness

공식 코드

Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity

https://github.com/so-cool/individualfairness

공식 코드

Cross-model Fairness: Empirical Study of Fairness and Ethics Under Model Multiplicity

https://github.com/soccernet/sn-mvfoul

공식 코드

Towards AI-Powered Video Assistant Referee System (VARS) for Association Football

https://github.com/social-futures-lab/skin-deep

공식 코드

Skin Deep: Investigating Subjectivity in Skin Tone Annotations for Computer Vision Benchmark Datasets

https://github.com/socialfoundations/error-parity

공식 코드

Unprocessing Seven Years of Algorithmic Fairness

https://github.com/som-shahlab/fairness_benchmark

공식 코드

An Empirical Characterization of Fair Machine Learning For Clinical Risk Prediction

https://github.com/som-shahlab/net_benefit_ascvd

공식 코드

Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare

https://github.com/sonyresearch/responsible_data_curation

공식 코드

Ethical Considerations for Responsible Data Curation

https://github.com/sophhan/imlsa_2024

공식 코드

Interpretable Machine Learning for Survival Analysis

https://github.com/sparkssss/DistroFair

공식 코드

Distribution-aware Fairness Test Generation

https://github.com/sparkssss/aequevox

공식 코드

AequeVox: Automated Fairness Testing of Speech Recognition Systems

https://github.com/spring-epfl/disparate-vulnerability

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Disparate Vulnerability to Membership Inference Attacks

https://github.com/spring-epfl/pots

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POTs: Protective Optimization Technologies

https://github.com/sprocketlab/fair-ws

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Mitigating Source Bias for Fairer Weak Supervision

https://github.com/sruthigorantla/FIGR

공식 코드

On the Problem of Underranking in Group-Fair Ranking

https://github.com/sruthigorantla/group-fair-pl

공식 코드

Optimizing Group-Fair Plackett-Luce Ranking Models for Relevance and Ex-Post Fairness

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.